9 of 9 Reinforcement Learning Jobs in the South East

Description The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm's data and analytics journey. As a part of CDAO, The Machine Learning Center of Excellence (MLCOE) partners across the firm to shape, create, and deploy Machine Learning Solutions for our most challenging business problems. This includes ensuring the quality, integrity, and … generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly. As a Summer Associate within the MLCOE, you will apply sophisticated machine learning methods … to a diverse range of complex domains, including natural language processing, large language models, speech recognition and understanding, reinforcement learning, and recommendation systems. You will collaborate closely with MLCOE mentors, business experts, and technologists, conducting independent research and deploying solutions into production. A strong passion for machine learning, solid expertise in deep learning with hands-on More ❯

paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment … we back each other to deliver impact. Make Wayve the experience that defines your career The role We're looking for a curious and motivated Reinforcement Learning Intern to help advance the next generation of decision-making systems for autonomous driving. In this role, you'll work embedded in a research team to develop scalable RL algorithms that … enable vehicles to learn complex behaviors directly from experience — both in simulation and the real world. The ideal candidate has experience in some combination of reinforcement learning, imitation learning, offline RL, or world modelling, and is motivated to apply cutting-edge research ideas to real-world embodied AI challenges. We're particularly interested in temporal credit assignment More ❯

working hours Based in Central London Over the course of 10 weeks, G-Research Summer Research Programme interns gain a unique insight into life as a Machine Learning (ML) practitioner at a leading quantitative finance research firm. Our full-time ML researchers use a wide range of tools and techniques in an applied setting, putting their expertise to use … on completion of their studies. Who are we looking for? The ideal candidate will, at a minimum, have experience in the following areas: A post-graduate degree in Machine Learning or a related discipline, or commercial experience developing novel machine learning algorithms. We will also consider exceptional candidates with a proven record of success in online data science … competitions, such as Kaggle. PhD level study is preferred Experience in one or more of deep learning, reinforcement learning, non-convex optimisation, Bayesian non-parametrics, NLP or approximate inference Excellent reasoning skills and mathematical ability are crucial: off-the-shelf methods don't always work with our data, so you will need to understand how to develop More ❯

AI Engineer - Remote We are currently working on an AI Engineer role with a global language and translation company. You will be designing, developing, and deploying cutting-edge machine learning solutions across the company.If you enjoy end-to-end ownership (from experimentation to deployment), working with AWS, Docker, MLflow, TensorFlow/PyTorch, and contributing to innovative projects with a … write and produce production-grade code in Python Experience with TensorFlow, PyTorch and Scikit-learn Experience with NLPs and LLMs Speech, Text or Audio data Strong knowledge of machine learning techniques and algorithms, including supervised and unsupervised learning, deep learning, and reinforcement learning More ❯

of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that … Testing the robustness of our safety techniques by training language models to subvert our safety techniques, and seeing how effective they are at subverting our interventions. Run multi-agent reinforcement learning experiments to test out techniques like AI Debate. Build tooling to efficiently evaluate the effectiveness of novel LLM-generated jailbreaks. Write scripts and prompts to efficiently produce … efforts Pick up slack, even if it goes outside your job description Care about the impacts of AI Strong candidates may also: Have experience authoring research papers in machine learning, NLP, or AI safety Have experience with LLMs Have experience with reinforcement learning Have experience with Kubernetes clusters and complex shared codebases Candidates need not have More ❯

in one or more programming languages. 3 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing …/algorithms in C++ and Python. Experience with an emphasis on algorithms, systems and tools for ML performance projections and evaluation. Experience designing or implementing components of a Deep Learning Compiler Stack (e.g., XLA, MLIR, TVM, ONNX Runtime). Experience in low-latency systems programming (e.g., C/C++) and optimizing data movement across the memory hierarchy (e.g., caches … HBM, I/O). Experience in performance engineering for ML/AI, including the design and optimization of GPU/TPU kernels, deep learning compilers, or low-latency systems infrastructure. About the job Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our More ❯

/orchestration tools such as Docker and Kubernetes. Proficiency in backend programming languages such as Go, Rust, Python, or C++. Familiarity with LLM inference pipelines, multi-agent architectures, or reinforcement learning environments is a strong plus. Knowledge of network optimization, data streaming, and caching architectures preferred. Excellent collaboration and communication skills. Ability to commit 20–30 hours per More ❯

in the field, using your knowledge of state-of-the-art techniques to solve problems. LLMs will be your bread and butter, customized with advanced RAG techniques, finetuning and reinforcement learning. You'll work closely with other engineers to build fast, and you'll use Python and Kubernetes to deploy systems in production. What you'll do Work with … LLMs understand and interact with the millions of lines of code that run Kraken, leveraging techniques at the cutting-edge of the technology like GraphRAG, agentic workflows, finetuning, and reinforcement learning Use classic ML and NLP techniques to complement and improve LLM systems Act as a center of excellence for the whole business in AI, as a floating More ❯

for our customers. You will use and improve multimodal LLMs to achieve new functionality for our customers and optimize their deployments (cloud and edge). Some of our deep learning models are truly tiny - the memory footprint of our smallest computer vision model is just 1MB. You will train and design more accurate models, while also enabling new and … team on the same software project. Nice To Have Trained neural networks that moved into production. Industry experience with efficient inference deployments (cloud or edge). Experience with Deep Reinforcement Learning. Benefits What we offer Competitive salary. Generous equity stake in the company. Relocation assistance. Choose your own laptop. 25 days of paid vacation time in addition to bank More ❯